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Journal articles on the topic 'Production engineering maintenance'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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1

Wöstmann, R., P. Strauss, and J. Prof Deuse. "Predictive Maintenance in der Produktion*/Predictive Maintenance in production." wt Werkstattstechnik online 107, no. 07-08 (2017): 524–29. http://dx.doi.org/10.37544/1436-4980-2017-07-08-48.

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Über neue Möglichkeiten der Vernetzung und Datenverarbeitung von Anlagen und -komponenten gewinnt die prädiktive Instandhaltung stetig an Bedeutung. Während sie insbesondere in der Luftfahrt sowie bei der Versorgungs- und Energietechnik schon seit Jahren zum Einsatz kommt, sind innerhalb der Produktion derzeit noch wenige Anwendungsfälle zu finden. Der Beitrag stellt die bisher ungenutzten Potentiale dar, indem branchenübergreifende Anwendungsfälle sowie deren Übertragbarkeit auf die Produktion und Voraussetzungen für eine erfolgreiche Einführung vorgestellt werden.   Due to new possibilities of connectivity and data processing of assets and components, predictive maintenance has gained a growing importance. While it has been used in aerospace, supply or energy technology for many years, there are still few applications to be found within production. This paper outlines unused potential in presenting a classification of existing predictive maintenance applications and their transferability to production as well as prerequisites for a successful implementation.

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2

Tapiero, Charles S. "Continuous quality production and machine maintenance." Naval Research Logistics Quarterly 33, no. 3 (August 1986): 489–99. http://dx.doi.org/10.1002/nav.3800330313.

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3

Ahmad, Rosmaini, and Shahrul Kamaruddin. "Structured maintenance engineering policy development based on a production machine process perspective." Journal of Quality in Maintenance Engineering 23, no. 2 (May 8, 2017): 180–94. http://dx.doi.org/10.1108/jqme-03-2016-0009.

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Purpose The purpose of this paper is to present the development of a maintenance engineering policy in the context of a decision support model based on a production machine process perspective. Design/methodology/approach The structure of the policy is called the maintenance decision support (MDS) model, which consists of three steps: initial setup, deterioration monitoring, and decision making. A detailed presentation of each step of the proposed model together with a real case example from the pulp manufacturing industry proves the applicability of the model. Findings Validation of the proposed MDS model is as follows. In Task 1 of Step 1, the cutting, sealing, and perforating line processes are classified as critical machining processes. The analysis of Task 2 of Step 1 found that cutting knife, bearing, and motor are classified as the components that most possibly contribute to the cutting appearance quality. In Task 3 of Step 1, it was found that the cutting knife is classified as a maintenance-significant component with non-repairable and single-component type characteristics. The result of Step 2 suggested that at the 29th hour of operating time, the decision of do-something was suggested. In the following step (Step 3), for the case of the cutting knife, which has been classified as a non-repairable type component, the decision to perform preventive replacement of cutting knife is recommended to be carried out at the 29th hour of operating time. Research limitations/implications The uniqueness of this model is that it systematically considers different machinery component(s) characteristics, including single- and multiple-component cases, repairable and non-repairable types, and functional or/and physical failure types, to make maintenance decisions. Practical implications The proposed MDS model provides a systematic guideline for identifying, evaluating, and monitoring, which makes maintenance-related decisions. Three significant maintenance decisions can be determined based on the proposed MDS model, which includes an appropriate time-to-perform maintenance, correct maintenance actions to be performed, and the right component required for maintenance (for multi-component cases). Originality/value One of the vital elements in considering the production machine process perspective toward the development of the MDS model is the need to use product output/quality characteristics for machine deterioration-monitoring and decision-making processes.

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4

Zhang, Jun, Zhao Hong Yan, and Zhang Jian Qiang. "IETM Technology is the Development Direction of Engineering Machinery Maintenance." Advanced Materials Research 823 (October 2013): 572–76. http://dx.doi.org/10.4028/www.scientific.net/amr.823.572.

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Based on the interactive electronic technical manual (IETM) characteristics of the analysis, combined with the current situation of China's engineering machinery repair, comparative analysis of technical advantages of using IETM technology in engineering machinery repair in data acquisition technology, from the speed, fault isolation efficiency and personnel's work efficiency and other aspects, discusses the necessity of its application; combined with IETM production standards, from the main creative part of IETM, such as information generation, information management, production of interactive interface, several aspects of publishing, explains IETM make the development process and the main production platform. By using the structure block diagram, showing the method of information production and information management mode, and the main modules in the block diagram and function are described; and discusses future development proposals.

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5

Wang, Chih-Hsiung. "Optimal production and maintenance policy for imperfect production systems." Naval Research Logistics 53, no. 2 (March 2006): 151–56. http://dx.doi.org/10.1002/nav.20124.

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6

IRAVANI, SEYED M. R., and IZAK DUENYAS. "Integrated maintenance and production control of a deteriorating production system." IIE Transactions 34, no. 5 (May 2002): 423–35. http://dx.doi.org/10.1080/07408170208928880.

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7

Zarrin, Mansour, and Ali Azadeh. "Simulation optimization of lean production strategy by considering resilience engineering in a production system with maintenance policies." SIMULATION 93, no. 1 (September 29, 2016): 49–68. http://dx.doi.org/10.1177/0037549716666682.

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Lean production aims are to reduce work-in-process and maintain close to zero inventories and resilience is about reacting quickly to disruptions impacting manufacturing systems. In this study, a manufacturing organization with maintenance strategy is simulated to evaluate the impacts of resilience engineering (RE) principles on lean practices. The process of simulation is conducted for different scenarios. Each scenario includes a set of resilience principles. Using computer simulation, many outputs are calculated namely, utility and availability of machines and maintenance operators, time in system, total cost, and number of failures. The optimal values of scenarios’ efficiencies are achieved using data envelopment analysis (DEA) model, which is a mathematical programming approach. The results of the DEA are validated by using principal component analysis. In addition, an analysis is performed to determine which factor of RE has the maximum effect on the system’s performance. The results show that the redundancy among the RE principles, has the maximum impact on the system’s performance. To the best of my knowledge, this is the first study that evaluates the performance of lean production considering RE in a production line with maintenance policies.

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8

Chang, Qing, Jun Ni, Pulak Bandyopadhyay, Stephan Biller, and Guoxian Xiao. "Maintenance Opportunity Planning System." Journal of Manufacturing Science and Engineering 129, no. 3 (February 7, 2007): 661–68. http://dx.doi.org/10.1115/1.2716713.

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Timely performance of preventive maintenance (PM) tasks is a critical element of manufacturing systems. Since the majority of PM tasks requires that equipment be stopped, these tasks can generally only be performed during nonproduction shifts, breaks, or other scheduled downtime. Thus, there is a trade-off between time dedicated to production and time available for preventive maintenance. One approach to mitigate this trade-off is to perform maintenance during scheduled production time by strategically shutting down equipment for short time periods. This research developed a systematic method on when to shut down equipment to do maintenance in an automotive assembly environment. It is called maintenance opportunity. The method incorporated real-time information about production and machine failure conditions. A simulation-based algorithm is developed by utilizing the buffer contents as well as machine starvation and congestion to obtain maintenance opportunities during production time.

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9

Macchi, Marco, Adolfo Crespo Márquez, Maria Holgado, Luca Fumagalli, and Luis Barberá Martínez. "Value-driven engineering of E-maintenance platforms." Journal of Manufacturing Technology Management 25, no. 4 (April 29, 2014): 568–98. http://dx.doi.org/10.1108/jmtm-04-2013-0039.

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Purpose – The purpose of this paper is to propose a methodology for the engineering of E-maintenance platforms that is based on a value-driven approach. Design/methodology/approach – The methodology assumes that a value-driven engineering approach would help foster technological innovation for maintenance management. Indeed, value-driven engineering could be easily adopted at the business level, with subsequent positive effects on the industrial applications of new information and communication technologies solutions. Findings – The methodology combines a value-driven approach with the engineering in the maintenance scope. The methodology is tested in a manufacturing case to prove its potential to support the engineering of E-maintenance solutions. In particular, the case study concerns the investment in E-maintenance solutions developed in the framework of a Supervisory Control and Data Acquisition system originally implemented for production purposes. Originality/value – Based on literature research, the paper presents a methodology that is implemented considering three different approaches (business theories, value-driven engineering and maintenance management). The combination of these approaches is novel and overcomes the traditional view of maintenance as an issue evaluated from a cost-benefit perspective.

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10

Nentwich, Corbinian, Maximilian Benker, Johannes Ellinger, Simon Zhai, Robin Kleinwort, Gunther Reinhart, and F. Michael Zäh. "Predictive Maintenance in der Produktion/Predictive Maintenance within the industrial value chain." wt Werkstattstechnik online 110, no. 03 (2020): 98–102. http://dx.doi.org/10.37544/1436-4980-2020-03-14.

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Ungeplante Maschinenausfälle führen zu Stillständen in der Produktion, die große Auswirkungen auf die Wertschöpfungskette eines Unternehmens haben. Der Einsatz von Predictive Maintenance (PdM) entlang dieser Kette erhöht die Maschinenverfügbarkeit und sichert einen reibungslosen Produktionsablauf. Im Rahmen verschiedener Forschungsprojekte am iwb werden Anwendungsfälle für PdM in der Fertigung, der Montage und der Produktionssteuerung betrachtet. Dieser Beitrag beleuchtet individuelle Herausforderungen, Lösungsansätze und Grenzen von PdM im produktionstechnischen Umfeld.   Unplanned machine downtimes can have a big impact on the value chain of a company. Predictive Maintenance (PdM) shows the potential to increase machine availability and secures smooth production processes. Different research projects at iwb examine applications of PdM within manufacturing and assembly, as well as the integration of such approaches in production planning. This article highlights individual challenges, solutions and limits of PdM within production.

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11

Yang, Ming-Feng, and Yi Lin. "Integrated inventory model with backorder and minimal repair in a supply chain." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 232, no. 3 (May 16, 2016): 546–60. http://dx.doi.org/10.1177/0954405416645997.

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This study explores the feasibility of applying an integrated inventory model with the consideration of incorporating production programs and maintenance to an imperfect process involving a deteriorating production system. The main target of this research is to build an integrated inventory model with the issues of backorder and repair. Additionally, our proposed model tries to provide an optimal number of shipments m and lower cost. Furthermore, this article offers the detailed discussion of two preventive maintenances of the production run period which are named as perfect preventive maintenance and imperfect preventive maintenance. Also, in this study, we develop various special cases that consider the failure rate such as Weibull, geometric and learning effect. Based on the results, the demand and production ratio influences the holding cost and purchase cost and has the highest impact on the integrated model.

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12

Sheu, Shey-Huei, Yuh-Bin Lin, and Gwo-Liang Liao. "Optimal number of production corrections before maintenance of imperfect production processes." International Journal of Advanced Manufacturing Technology 30, no. 3-4 (January 21, 2006): 319–27. http://dx.doi.org/10.1007/s00170-005-0086-x.

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13

Oke, Sunday Ayoola, Ayokunle Bamigbaiye, and Oluwafemi Isaac Oyedokun. "A MATHEMATICAL MODEL FOR EVALUATING ACCELERATED WEAR DUE TO INEFFICIENT MAINTENANCE." TRANSPORT 21, no. 2 (June 30, 2006): 105–11. http://dx.doi.org/10.3846/16484142.2006.9638050.

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This paper examines accelerated wear due to inefficient maintenance practice in the engineering organization, with a special focus on plant machinery. It considers some important parameters, mathematical relations and how to reduce the effect of poor maintenance practices on plant machinery. Mathematical tools of calculus, series, statistics, and variation were utilized in the development of the model. The result shows that poor maintenance practices increase accelerated wear in plant machinery while good maintenance is aided by planned maintenance, well‐stocked inventory of spare parts, good production procedures, extended plant life, etc. This work is limited in scope since it considers a limited number of parameters as measures of wear. The paper is valuable to the maintenance manager and practitioners who intend to produce/manufacture and at the same time minimize the accelerated wear in production machinery by close monitoring, and using the model as a tool. The work is of immense benefits to managers in process industries, particularly in oil and gas exploration activities. The work is new, presenting a simple approach for easy adaptation in the industry. The approach utilized is not yet documented in the maintenance engineering literature. Thus, a new area of research is opened up for research explorations for the members of the maintenance engineering community

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14

Yang, Zimin, Qing Chang, Dragan Djurdjanovic, Jun Ni, and Jay Lee. "Maintenance Priority Assignment Utilizing On-line Production Information." Journal of Manufacturing Science and Engineering 129, no. 2 (March 24, 2006): 435–46. http://dx.doi.org/10.1115/1.2336257.

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Maintenance management has a direct influence on production performance. Existing works have not systematically taken the on-line production information into consideration in determining maintenance work-order priority, which is often assigned either through an ad hoc approach or using largely heuristic and static methods. In this paper, we first present a metric that can be used to quantitatively evaluate the effects of different maintenance priorities. Based on this index, one can employ a search algorithm to obtain maintenance work-order priorities that will lead to improved productivity within the optimization horizon. These concepts and methods are validated through simulation experiments and implementation in a real industrial facility. The results show that the effective utilization of on-line production data in dynamic maintenance scheduling can yield visible production benefit through maintenance priority optimization.

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15

Carr, Bruce A., Thomas M. Houlihan, and Michael A. Polini. "CAD/CAM in Phased Maintenance." Journal of Ship Production 7, no. 04 (November 1, 1991): 234–47. http://dx.doi.org/10.5957/jsp.1991.7.4.234.

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The authors' company is a medium-sized engineering company specializing in naval ship repair. The bulk of corporate work centers on the Phased Maintenance (PM) of three classes of ships. Typically, each PM contract covers three to five different ships per class scheduled for 90-day Availabilities at approximately one-year intervals over a period of five years. The type of work to be performed during each Phased Maintenance Availability (PMA) falls into one of two categories: ship alterations or ship repairs. The first group, ship alterations, is characterized by detailed, long-lead engineering and planning efforts, typically beginning 540 days prior to the vessels's arrival. The second group, ship repairs, makes up the other end of the spectrum with short lead times and compressed service details. The majority of repair items are identified 60 days prior to an Availability, while some are not determined until after the vessel has arrived in the shipyard. The engineering department that services PMA work is composed of three disciplines: structural, mechanical and electrical. The mechanical discipline is further subdivided into the areas of machinery and piping/HVAC. While the nature of PMA work within each discipline is peculiar to the application, the process is similar in each. Reference information is gathered and verified, technical analysis is provided where necessary, and detailed drawings are prepared and submitted for Navy approval prior to shipyard production. All drawings are developed using two-dimensional drafting techniques at various sites by teams of computer-aided design (CAD) input operators utilizing color graphic workstations on a multi-shift basis as required by the workload. Completed drawings are transferred to the engineering site over a network link, where additional workstations are available for engineers to check and correct them as necessary

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16

Lee, Tzu-Hsien. "Optimal production run length and maintenance schedule for a deteriorating production system." International Journal of Advanced Manufacturing Technology 43, no. 9-10 (October 7, 2008): 959–63. http://dx.doi.org/10.1007/s00170-008-1773-1.

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17

Ahmadi, Reza, and Mitra Fouladirad. "Maintenance planning for a deteriorating production process." Reliability Engineering & System Safety 159 (March 2017): 108–18. http://dx.doi.org/10.1016/j.ress.2016.11.001.

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18

DAS, TAPAS K., and SUDEEP SARKAR. "Optimal preventive maintenance in a production inventory system." IIE Transactions 31, no. 6 (June 1999): 537–51. http://dx.doi.org/10.1080/07408179908969857.

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19

Yao, Xiaodong, Xiaolan Xie, Michael C. Fu, and Steven I. Marcus. "Optimal joint preventive maintenance and production policies." Naval Research Logistics (NRL) 52, no. 7 (August 22, 2005): 668–81. http://dx.doi.org/10.1002/nav.20107.

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20

Yalaoui, Alice, Khalil Chaabi, and Farouk Yalaoui. "Integrated production planning and preventive maintenance in deteriorating production systems." Information Sciences 278 (September 2014): 841–61. http://dx.doi.org/10.1016/j.ins.2014.03.097.

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21

Aghezzaf, El-Houssaine, and Najib M. Najid. "Integrated production planning and preventive maintenance in deteriorating production systems." Information Sciences 178, no. 17 (September 2008): 3382–92. http://dx.doi.org/10.1016/j.ins.2008.05.007.

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22

Lu, Zhi Qiang, and Yue Jun Zhang. "A Joint Model of Production and Preventive Maintenance Plan." Advanced Materials Research 156-157 (October 2010): 18–23. http://dx.doi.org/10.4028/www.scientific.net/amr.156-157.18.

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We integrated run-based preventive maintenance (PM) into the production plan at the tactical level. The production plan was based on the single level capacitated lot-sizing problem (CLSP). We assumed the system reliability should be kept above certain threshold value to ensure the feasibility of the production plan; the reliability would be affected only by system running. Thus, PM would be triggered by the reliability requirement and the accumulated running time. We established this relationship as a nonlinear integer constraint in the joint model. We also proposed a branch and bound algorithm using CPLEX to solve the model. Finally, a numerical example was given to illustrate the difference between run-based and time-based PM.

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23

Njike, Achille N., Robert Pellerin, and Jean Pierre Kenne. "Maintenance/production planning with interactive feedback of product quality." Journal of Quality in Maintenance Engineering 17, no. 3 (August 16, 2011): 281–98. http://dx.doi.org/10.1108/13552511111157399.

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PurposeThis paper seeks to develop an optimal stochastic control model where interactive feedback consists of the quantity of flawless and defective products. The main objective of this study is to minimize the expected discounted overall cost due to maintenance activities, inventory holding and backlogs.Design/methodology/approachThe model differs from similar research projects in that, instead of age‐dependent machine failure, it considers only defective products as feedback into the optimal model for maintenance and production planning. In this paper a near optimal control policy of the system through numerical techniques is obtained.FindingsIn this paper, a new model in which the system's retroaction is the quantity of defective products is presented, considering that defective products are a consequence of global manufacturing system deterioration. Instead of taking into account machine failure and human error separately, it considers a defect in product as being the consequence of a combined failure; this consideration allows one to be more realistic by merging all failure parameters into a single one. A new stochastic control model, which focuses on defective products, inventory, and backlog, has been developed.Research limitations/implicationsThis approach extended the concept of hedging point policy to the quantity of defective products combined with preventive and corrective maintenance strategies. The control policy obtained has a bang bang structure and is completely known for given parameters.Originality/valueThe integration of maintenance and production strategies has been mainly focused on the machine. Many research projects have been focusing on the age when dealing with machine failure. It is considered as the main target of the cost reduction in maintenance engineering departments. The originality of this paper is the taking into account of all operational failures into the same optimization model. It brings a value added to high level of maintenance and for operation managers who need to consider all failure parameters before taking decisions related to cost.

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24

Chen, Xiaohui, Lei Xiao, Xinghui Zhang, Weixiao Xiao, and Junxing Li. "An integrated model of production scheduling and maintenance planning under imperfect preventive maintenance." Eksploatacja i Niezawodnosc - Maintenance and Reliability 17, no. 1 (January 1, 2015): 70–79. http://dx.doi.org/10.17531/ein.2015.1.10.

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25

Savsar*, M. "Modelling of multi-stage production lines with maintenance operations." International Journal of Computer Integrated Manufacturing 21, no. 4 (June 2008): 396–406. http://dx.doi.org/10.1080/09511920701575112.

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Jin, Yu-Lan, Zu-Hua Jiang, and Wen-Rui Hou. "Integrating flexible-interval preventive maintenance planning with production scheduling." International Journal of Computer Integrated Manufacturing 22, no. 12 (December 2009): 1089–101. http://dx.doi.org/10.1080/09511920903207449.

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27

Kollatsch, Christian, and Philipp Klimant. "Efficient integration process of production data into Augmented Reality based maintenance of machine tools." Production Engineering 15, no. 3-4 (February 17, 2021): 311–19. http://dx.doi.org/10.1007/s11740-021-01026-6.

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AbstractWith the increasing requirements on machine tools such as higher complexity, individuality and digitization, their maintenance becomes also more complex, which increases time consumption and demands special knowledge. The maintenance engineer can be supported in this process using the Augmented Reality (AR) technology, mobile devices and suitable production data. This requires the integration and adaptation of the maintenance documentation as well as further production systems and their data such as the CAD system, product data management (PDM) system, manufacturing execution system (MES) and CNC. For this purpose, a method is developed that allows an efficient integration process of various production data into an AR supported maintenance documentation. This includes concepts for the integration process of different production systems and data into an AR maintenance system as well as the design of the AR maintenance system architecture. Basis is the analysis of the required production and AR systems, data and processes. The aim of the method is to reduce the high expenditure of the overall planning process and the necessary expertise of the maintenance planner of the AR technology. The developed method is verified with different maintenance scenarios, production systems and data as well as machine tools and AR devices.

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28

Yang, Won Seok, Dae E. Lim, and Kyung C. Chae. "Maintenance of multi-state production systems deteriorated by random shocks and production." Journal of Systems Science and Systems Engineering 20, no. 1 (December 6, 2010): 110–18. http://dx.doi.org/10.1007/s11518-010-5143-9.

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29

Drogovoz, P. A., N. S. Efimova, and V. D. Kalachanov. "Assessment of Production Program Feasibility in Aviation Engineering." Herald of the Bauman Moscow State Technical University. Series Mechanical Engineering, no. 2 (131) (April 2020): 88–108. http://dx.doi.org/10.18698/0236-3941-2020-2-88-108.

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The purpose of the study was to analyze the effective development of the production potential of the domestic industry of aviation engineering. We developed a method for calculating the summarizing indicators of assessing the feasibility of production programs of the aviation industry at the level of technological conversions and types of aircraft production. The application of such method will make it possible to more reasonably determine the material consumption of new types of aviation products and the productivity of new equipment, and, ultimately, assess the feasibility of promising production plans. Monitoring of production indicators of the domestic aviation engineering industry will encourage new research in the field of organizing the development, production and maintenance of hi-tech products, taking into account its specificity. Although plenty of important scientific research has been carried out by scientists in the field of organization of production at enterprises, there are currently unsolved problems of industrial-technological nature

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30

Nuraddin, Yusifov Samad. "PECULIARITIES OF PRODUCTION AND TECHNICAL PRODUCTION AND TECHNICAL EXPLOITATION OF THE USE OF TECHNOLOGY IN THE AGROTECHSERVICE ENTERPRISE." HERALD OF KHMELNYTSKYI NATIONAL UNIVERSITY 296, no. 4 (June 2021): 88–94. http://dx.doi.org/10.31891/2307-5740-2021-296-4-14.

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The purpose of the article is to improve the production and technical exploitation of the machine-tractor fleet and the efficient use of machinery in the service area with the use of application of resuscitation techniques. The methodology and methods used are the theoretical and methodological basis of the research work of our country and foreign scientists on the technical maintenance of agricultural production, the organization and effective functioning of the institutions implementing it. Here a number of methods of analysis of mass service theory and graph theory are used. The main scientific novelty of the results is the use of integrated indicators to mechanize technological processes in the context of existing structural features of agricultural production, to increase the operating level of the machine-tractor fleet. The production and technical exploitation depends on the level of technical maintenance of the process. The results of the research are joint review of “production and technical exploitation” and resuscitation techniques in ensuring the mechanization of technological processes in the context of existing structural features of agricultural production; the use of a comprehensive indicator for assessing the operational level of the machine-tractor fleet; development of the model of production and technical exploitation of the fleet based on four groups that characterize the usefulness of organizational, technical and technological measures, as well as methods of increasing the level of technical service of various economic entities to ensure the quality of the machine-tractor fleet operation: – Existing forms of technical and technological classification of mechanization of production processes in agriculture and increasing the intensity of use of machines in established engineering service facilities; – Improvement of production and technical exploitation of machine-tractor fleet of service enterprises operating in economic climatic conditions and improvement of use of machines with application of resuscitation techniques; – Ensure that labor costs and maintenance and repair in the manufacturing process are lower than the cost of 15 manat per conventional ha etalon; – Ensure the performance of the whole complex of mechanized work with the effective use of the machine-tractor fleet.

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Lei, Yong, Jianbo Liu, Jun Ni, and Jay Lee. "Production line simulation using STPN for maintenance scheduling." Journal of Intelligent Manufacturing 21, no. 2 (December 12, 2008): 213–21. http://dx.doi.org/10.1007/s10845-008-0194-1.

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32

Purohit, Bhushan S., and Bhupesh Kumar Lad. "Production and maintenance planning: an integrated approach under uncertainties." International Journal of Advanced Manufacturing Technology 86, no. 9-12 (February 10, 2016): 3179–91. http://dx.doi.org/10.1007/s00170-016-8415-9.

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33

Panevnyk, O. V., and D. O. Panevnyk. "Analysis of tendencies of oil and gas engineering development." Oil and Gas Power Engineering, no. 1(33) (September 3, 2020): 90–100. http://dx.doi.org/10.31471/1993-9868-2020-1(33)-90-100.

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Based on the study of the dynamics of global costs for oilfield equipment, it was found that its production shows slow growth, the largest share of oil and gas machinery is in North America, and the largest segment of production belongs to the manufacture of equipment for collecting and transporting hydrocarbons and pipe products. In the process of analysis of the nomenclature and geography of production of machines, mechanisms, individual components and parts of drilling and oil and gas equipment, the inconsistency of the level of development of oil and gas engineering in Ukraine with the needs of the fuel and energy complex is shown. The required level of production of equipment and spare parts directly depends on the quality of maintenance of oil and gas machines, which with the development of new technologies for the development of hydrocarbon fields should increase. The main reasons for failures of oil and gas equipment are the lack of proper maintenance. Domestic oil companies are focused on the import of oil equipment, and a negative problem for the development of the domestic market of oil services is the reduction of their own production of oil and gas equipment. One of the most important competitive advantages of domestic service companies is a lower level of prices for services, as well as a deeper knowledge of the specifics and features of local conditions for the development of hydrocarbon deposits. An important aspect of the development of the service market is the transition to innovative technologies in the field of geological engineering and drilling. In accordance with the development trends of the world oil and gas engineering industry, the staffing requirements of service companies are increasing. Given the complexity of mining and geological conditions for the development of hydrocarbon deposits, the development of new technologies for oil and gas production requires increasing attention to training specialists who are aware of modern methods of design, operation and maintenance of oil and gas equipment.

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34

Zheng, Jiafei, Hongbing Yang, Qingsong Wu, and Ziyang Wang. "A two-stage integrating optimization of production scheduling, maintenance and quality." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 234, no. 11 (June 7, 2020): 1448–59. http://dx.doi.org/10.1177/0954405420921733.

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During the process of actual production, production scheduling, preventive maintenance and quality control have a close interaction with each other and thus need to be integrated for improving manufacturing system performance. The aim of this article is to jointly optimize the job sequence, the preventive maintenance locations, the preventive maintenance interval and decision variables of control chart such that the expected cost per unit time and penalty cost due to schedule delay are minimized. A two-stage integrating optimization model of production scheduling, maintenance and quality in a single machine system is developed. A control chart is adopted to monitor the whole process with Taguchi’s loss function estimating the quality cost of each condition and perfect preventive maintenance activity is conducted at the end of each interval. A genetic algorithm is designed to solve this model in order to obtain the optimal job sequence and the locations of preventive maintenance. Numerical examples and thorough sensitivity analyses are provided to illustrate the proposed integrated model. Finally, the efficiency of the proposed two-stage integration model is verified by the comparison of the stand-alone model under the same condition. Compared with the stand-alone model, the proposed integrated method can save the cost rate by 12%–42% under five different situations.

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BEN-DAYA, M. "Integrated production maintenance and quality model for imperfect processes." IIE Transactions 31, no. 6 (June 1999): 491–501. http://dx.doi.org/10.1080/07408179908969852.

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Rosqvist, T., K. Laakso, and M. Reunanen. "Value-driven maintenance planning for a production plant." Reliability Engineering & System Safety 94, no. 1 (January 2009): 97–110. http://dx.doi.org/10.1016/j.ress.2007.03.018.

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Zamboni, Nicola, Nigel Mouncey, Hans-Peter Hohmann, and Uwe Sauer. "Reducing maintenance metabolism by metabolic engineering of respiration improves riboflavin production by Bacillus subtilis." Metabolic Engineering 5, no. 1 (January 2003): 49–55. http://dx.doi.org/10.1016/s1096-7176(03)00007-7.

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Cheng, Guo Qing, Bing Hai Zhou, and Ling Li. "Integrated production, quality control and condition-based maintenance for imperfect production systems." Reliability Engineering & System Safety 175 (July 2018): 251–64. http://dx.doi.org/10.1016/j.ress.2018.03.025.

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Wang, Huan Yun, and Chun Hui Pan. "Maintenance of Hydraulic Systems on Machine Tools." Advanced Materials Research 717 (July 2013): 375–77. http://dx.doi.org/10.4028/www.scientific.net/amr.717.375.

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Proper maintenance of hydraulic equipments has a great significance to increase ratio of perfectness and utilization, ensure the quality of the project, extend service life, improve production efficiency and reduce production costs. The authors in this paper discuss the scientific measures to keep equipments in good condition and ensure workplace safety from the angle of hydraulic systems maintenance. It has reference value for proper care and maintenance of hydraulic systems on machine tools in the factorys.

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Haider, Abrar, and Andy Koronios. "E-Prognostics: A Step towards E-Maintenance of Engineering Assets." Journal of Theoretical and Applied Electronic Commerce Research 1, no. 1 (April 1, 2006): 42–55. http://dx.doi.org/10.3390/jtaer1010005.

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Reliability of manufacturing or production processes is heavily dependent upon the flawless operation of asset plant and equipment utilised in the processes. Nevertheless, continuous and seamless flow of information, aimed at real time access to process stakeholders provides the foundation for effective management of these assets. An essential requirement in this regard is the continuous availability of the condition monitoring information and its analyses in order to predict failure conditions as soon as the asset starts deviating away from its standard operational behaviour. This paper presents an integrated approach for prognostics based on radio frequency identification (RFID) technology. It presents an architecture aimed at introducing information processing capabilities at the asset level, thereby equipping the asset to be proactive in identifying its maintenance requirements wirelessly rather than relying on human interaction to examine the asset for irregularities.

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Sun, Y., L. Ma, and J. Mathew. "Determination of optimal preventitive maintenance strategy for serial production lines." Australian Journal of Mechanical Engineering 5, no. 2 (January 2008): 97–103. http://dx.doi.org/10.1080/14484846.2008.11464538.

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Sridhar, S. "Determination of aggregate preventive maintenance programs using production schedules." Computers & Industrial Engineering 14, no. 2 (January 1988): 193–200. http://dx.doi.org/10.1016/0360-8352(88)90028-9.

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Aigboje, Eddy, Paul A. Ugboya, and Martins Odiamenhi. "Quality Maintenance of Production Equipment: A Case Study of Bendel Feeds and Mills, Ewu, Edo State." Journal of Advances in Science and Engineering 2, no. 2 (August 30, 2019): 1–7. http://dx.doi.org/10.37121/jase.v2i2.54.

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This paper analyses the quality maintenance in Bendel Feeds and Mills, Ewu, Edo State, with a view of designing a robust maintenance process and schedule to enhance production equipment in the company. The specific objectives were to determine the failure rate in the company production equipment, establish the appropriate maintenance process needed to reduce failure rate, investigate whether the current material handling methods and practices permit high maintenance turnover and to proffer useful suggestions and ideas on how to effectively maintain production equipment in the company. Data obtained were used to analyse the materials handling equipment failure rate, MTTR, MTBF, availability, failure mode and work station. The results showed that the failure rate is more in bucket elevator equipment than other materials handling equipment. It was observed that the plant organisational structure is area controlled instead of centre controlled organisation, which is one of the problems of the plant maintenance policy adopted by the company. Maintenance of materials handling equipment of the plant can be better achieved through modified planned preventive maintenance, condition base maintenance (predictive) and equipment inspection. This analysis will be of tremendous help to practicing maintenance engineering.

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Ansari, Fazel, Robert Glawar, and Tanja Nemeth. "PriMa: a prescriptive maintenance model for cyber-physical production systems." International Journal of Computer Integrated Manufacturing 32, no. 4-5 (February 20, 2019): 482–503. http://dx.doi.org/10.1080/0951192x.2019.1571236.

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Rodríguez Piñeiro, Alberto Julio, Armando Díaz Concepción, Leisis Villar Ledo, and Jorge Enrique Tamayo Mendoza. "Methodology for maintenance management based on diagnostic criteria." DYNA 86, no. 211 (October 1, 2019): 208–14. http://dx.doi.org/10.15446/dyna.v86n211.77704.

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The present research was as objective to design a methodology for diagnostic of maintenance management, to can apply any field of production or service. In the design a study realized in different methodology was used expect tools work, storm brain and the Delphi method. The methodology obtained called Methodology by Diagnostic Criteria had as main characteristics to consist of a checklist (see Diagnostic sheet made in Excel) of the quantitative type, consisting of 5 functional areas, 21 dimensions, 38 criteria and 186 diagnostic criteria, simple to contextualize any field of action of the maintenance engineering. The methodology was applied in the transport area of an Ecuadorian university.

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Sitompul, Carles, and El‐Houssaine Aghezzaf. "An integrated hierarchical production and maintenance‐planning model." Journal of Quality in Maintenance Engineering 17, no. 3 (August 16, 2011): 299–314. http://dx.doi.org/10.1108/13552511111157407.

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Gento, Angel M., and Alfonso Redondo. "Rough sets and maintenance in a production line." Expert Systems 20, no. 5 (November 2003): 271–79. http://dx.doi.org/10.1111/1468-0394.00251.

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Khan, F. "Risk-based maintenance of ethylene oxide production facilities." Journal of Hazardous Materials 108, no. 3 (May 20, 2004): 147–59. http://dx.doi.org/10.1016/j.jhazmat.2004.01.011.

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Li, Li, and Li Xin Wang. "Application of BIM Technology in Green Building Engineering Construction." Advanced Materials Research 860-863 (December 2013): 1301–5. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.1301.

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BIM is a direct application of information technology in construction industry. It covers the whole life cycle of engineering construction, including project planning, design, construction, operation and maintenance. BIM improves the engineering quality, saves cost and improves production efficiency. In this paper, we will discuss the application of BIMs collaborative integrated function in engineering construction project and BIMs future application.

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Liyanage, Jayantha P. "Operations and maintenance performance in production and manufacturing assets." Journal of Manufacturing Technology Management 18, no. 3 (March 20, 2007): 304–14. http://dx.doi.org/10.1108/17410380710730639.

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